Abstract
Collection and maintenance of biodiversity data is in need for automation. We present first results of an automated and model-free approach to the species identification from herbarium specimens kept in herbaria worldwide. Methodologically, our approach relies on standard methods for the detection and description of so-called interest points and their classification into species-characteristic categories using standard supervised learning tools. To keep the approach model-free on the one hand but also offer opportunities for species identification even in very challenging cases on the other hand, we allow to induce specific knowledge about important visual cues by using concepts of active learning on demand. First encouraging results on selected fern species show recognition accuracies between 94 % and 100 %.
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Matteo Spampani Alessio Anzivino: Hog-processing. http://hogprocessing.altervista.org. Accessed 15 Mar 2016
Backes, A.R., Casanova, D., Bruno, O.M.: Plant leaf identification based on volumetric fractal dimension. Int. J. Pattern Recogn. Artif. Intell. 23(06), 1145–1160 (2009)
Belhumeur, P.N., et al.: Searching the world’s Herbaria: a system for visual identification of plant species. In: Forsyth, D., Torr, P., Zisserman, A. (eds.) ECCV 2008, Part IV. LNCS, vol. 5305, pp. 116–129. Springer, Heidelberg (2008)
Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2005, CVPR 2005, vol. 1, pp. 886–893. IEEE (2005)
Goëau, H., Bonnet, P., Joly, A., Boujemaa, N., Barthélémy, D., Molino, J.-F., Birnbaum, P., Mouysset, E., Picard, M.: The imageclef 2011 plant images classi cation task. In: ImageCLEF 2011 (2011)
Goëau, H., Joly, A., Selmi, S., Bonnet, P., Mouysset, E., Joyeux, L., Molino, J.-F., Birnbaum, P., Bathelemy, D., Boujemaa, N.: Visual-based plant species identification from crowdsourced data. In: Proceedings of the 19th ACM International Conference on Multimedia, pp. 813–814. ACM (2011)
Joachims, T.: Making large scale svm learning practical. Technical report, Universität Dortmund (1999)
Joachims, T.: Svmlight (2008). http://svmlight.joachims.org/. Accessed 14 Nov 2015
Kadir, A., Nugroho, L.E., Susanto, A., Santosa, P.I.: Leaf classification using shape, color, and texture features (2013). arXiv preprint arXiv:1401.4447
David, G.: Lowe: distinctive image features from scale-invariant keypoints. Int. J. Comput. Vision 60(2), 91–110 (2004)
Mikolajczyk, K., Schmid, C.: A performance evaluation of local descriptors. IEEE Trans. Pattern Anal. Mach. Intell. 27(10), 1615–1630 (2005)
Muséum national d’Histoire naturelle, Paris (France). Collection: Vascular plants (P). Specimens
Nilsback, M.-E., Zisserman, A.: Automated flower classification over a large number of classes. In: Sixth Indian Conference on Computer Vision, Graphics and Image Processing, ICVGIP 2008, pp. 722–729. IEEE (2008)
O’Dell, W.: Imagej plugins: Template-matching. http://rsb.info.nih.gov/ij/plugins/template-matching.html. Accessed 15 Mar 2016
Rasband, W.S.: Imagej. U. S. National Institutes of Health, Bethesda, Maryland, USA (2015). http://imagej.nih.gov/ij/. Accessed 14 Nov 2015
Saalfeld, S.: Javasift (2015). https://github.com/axtimwalde/mpicbg. Accessed 14 Nov 2015
Settles, B.: Active learning literature survey. Computer Sciences Technical report 1648, University of Wisconsin-Madison (2010)
Tong, S., Koller, D.: Support vector machine active learning with applications to text classification. J. Mach. Learn. Res. 2(Nov), 45–66 (2001)
Wang, X., Han, T.X., Yan, S.: An hog-lbp human detector with partial occlusion handling. In: 2009 IEEE 12th International Conference on Computer Vision, pp. 32–39. IEEE (2009)
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Grimm, J., Hoffmann, M., Stöver, B., Müller, K., Steinhage, V. (2016). Image-Based Identification of Plant Species Using a Model-Free Approach and Active Learning. In: Friedrich, G., Helmert, M., Wotawa, F. (eds) KI 2016: Advances in Artificial Intelligence. KI 2016. Lecture Notes in Computer Science(), vol 9904. Springer, Cham. https://doi.org/10.1007/978-3-319-46073-4_16
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DOI: https://doi.org/10.1007/978-3-319-46073-4_16
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